2 citations · 3 across the 17 of their papers we have counts for
11 papers · 1 filter
Design Docs Are All You Need: An AI-native Machine-Learning Performance Tool
Samuel Kushnir, Kimia Noorbakhsh, Kavya Sreedhar +6
Machine-learning performance modeling is a uniquely hostile terrain for long-lived software: the assumptions baked into today's abstractions are invalidated by tomorrow's models an…
Compiling Bioinformatics Recurrences
Bala Vinaithirthan, Shiv Sundram, Sneha Goenka +1
Many bioinformatics algorithms, such as sequence alignment and structure prediction, can be expressed as recurrence equations over a dynamic programming matrix. Efficient implement…
Partitioning Unstructured Sparse Tensor Algebra for Load-Balanced Parallel Execution
Atharva Chougule, Alexander J Root, Rubens Lacouture +3
Sparse tensor algebra is challenging to efficiently parallelize due to the irregular, data-dependent, and potentially skewed structure of sparse computation. We propose the first p…
Optimal Software Pipelining and Warp Specialization for Tensor Core GPUs
Rupanshu Soi, Rohan Yadav, Fredrik Kjolstad +4
GPU architectures have continued to grow in complexity, with recent incarnations introducing increasingly powerful fixed-function units for matrix multiplication and data movement…
Cyclotron: Compilation of Recurrences to Distributed and Systolic Architectures
Shiv Sundram, Akhilesh Balasingam, Nathan Zhang +2
We present Cyclotron, a framework and compiler for using recurrence equations to express streaming dataflow algorithms, which then get portably compiled to distributed topologies o…
Decoupling Data Layouts from Bounding Volume Hierarchies
Christophe Gyurgyik, Alexander J Root, Fredrik Kjolstad
Bounding volume hierarchies are ubiquitous acceleration structures in graphics, scientific computing, and data analytics. Their performance depends critically on data layout choice…